Keywords: Process Models, Transformer models, Multimodal Evidence, Process Representation
Astract: Stakeholders can struggle to understand and engage with process models due to a mismatch between the technical language used and their own domain-specific jargon and personal communication styles. The paper explores the application of transformer-based architectures to enhance the representation of process models and additional multimodal process data by tailoring them to the language of stakeholders. We present an approach that personalizes process model representations through two types of paraphrasers: one that aligns with domain-specific jargon and another that adapts to individual stakeholder styles. We developed a golden dataset from process model-stakeholder interaction simulation and a silver dataset using large language models to train and validate our approach. Initial findings suggest that these methods could enhance stakeholder engagement and contribute to better teaching of process mining and procedural thinking.

Keywords: Textbook, Conceptual Modeling, Ontology-Guided Modeling

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Keywords: data strategy, data management, semiotic triangle
Astract: It appears that, in an increasingly digital world, data is becoming more and more important for organizations. In several real-world cases in the Netherlands, we have seen that organizations struggle with issues such as: a) What data do we have? b) Which data do we need for value creation? c) Which strategic choices do we make around using data? d) Which strategic choices do we make around managing data as an asset? And e) Which skills do our people need in light of the previous items? The context for these organizations is different, but the challenges are the same. Our position is that the use of models can help to get to grips with the complexity of the aforementioned challenges. In this paper we explore a) the relationship between data and models, and b) a framework that connects data management as a means to care for data as an asset, and data as a means to achieve strategic objectives of the organization. In developing the latter, we follow a design science approach; we explore cases to understand challenges and requirements for such a framework as well as show how the framework helped to solve the challenges in these organizations.

Keywords: Process Mining, Multi-Modal Segmentation, Conceptual Modeling